Employee Engagement of AI at Scale - Karen Stroup, Chief Digital Officer, WEX @Generative AI World

When I take a step back and I think about it, and to date myself a little bit, I think about the sci-fi movies where people are moving things around on the screen and answers are magically appearing, and it seemed so unbelievable. Fast forward to today, and that fiction is now a reality. We now have a colleague who's sitting there coaching us, providing us and automating answers for us, never needs a coffee break. When you take a step back and think about the change from fiction to reality, and that AI is no longer a buzzword, it's actually helping augment and improve our lives, it's pretty incredible. But here's the catch: AI isn't just magically going to happen. That fiction isn't going to just become reality. The power is within you to capitalize on that potential of AI. It depends upon you, it depends upon your employees, and it depends upon your commitment to driving change. So with that, today I want to talk about how we can use employee engagement to ensure that this powerful tool serves us and not the other way around. A little bit of audience participation, it's really easy I promise. Please raise your hand if when you talk to your employees you get mixed feelings about AI. Well, I know this is certainly true at WEX. Talking to some people, you have one group who are all in, they are excited, they light up, they believe that AI is going to change their lives, it is going to change their work. These are the curious ones, those eager to embrace what's possible. You have the other end of the spectrum, we'll call them the skeptics, those who are really uncertain about technology. They are saying there is no way I'm going to use this, I don't know what it means, and their fears are real. They don't understand the technology, they don't understand the data, they don't know what it's going to mean for their job or their future, and they're coming from a place where they're really scared. And then you have the largest group, those in the middle, who are uncertain about what it means but they're open, they're curious, so they are the ones who aren't jumping in but aren't sure where to get started, but are influenceable. As we think about this, we start with understanding who our employees are and where they're coming from, and this forms the foundation for how we're approaching AI. This informs our strategy and our goals. We have three goals around AI, which I'll talk about in just a moment, but the most fundamental of the three is the one around our employees. Our goal for 2024 on employees is to ensure 100% of WEX employees are trained in AI and are inspired, not scared, by the potential of AI. We believe by starting with the employees, that will get the flywheel going, that will drive adoption, drive the act of use, drive the experimentation, and ultimately the impact. How did we approach this? We started with making this a strategic priority. It starts at the top. You heard Melissa, who's our CEO, and Shakar, our board member, on stage this morning. If you weren't there, let me go back in time. Melissa's been our CEO for 11 years, and when she first became CEO, Shakar would send her articles on a daily basis about company failures, and she was kind of like, what is this all about? But the message was that complacency kills, and thoughtful risk-taking, that culture of having to reinvent ourselves, became a really important part of Melissa's leadership and the culture of WEX. Data and AI have been an important strategic priority for WEX for a long time. It's embedded in everything we do, in our fraud prevention and detection, in our credit monitoring and adjudication, and marketing. But at the end of 2023, we had a really pivotal point. What they didn't say on stage: they had a lunch, and Melissa called me on her way home and said, 'Hey Karen, you really believe in gen AI and what's possible. We want to have a bold goal and make this a huge strategic priority for us going forward.' I was like, 'Okay, what are you thinking?' She said, 'I don't know, but we know that AI is going to change our future, and we want to lean into it. We want to be on the side that it's possible, and it's going to come faster than we expect, and we'll win because of that.' So that was the direction. With a few members in the audience here, we took a step back and said, 'Okay, what do we want to do with this?' What we felt confident in is by setting bold goals, we would achieve more even if we underperformed the bold goal a little bit. That was much better than setting a low bar and an incremental step forward. We won the bold goal. As I said, we had three goals: one was about increasing productivity, the second was reimagining customer experiences, and the third was around the employees. That employee piece, which we're talking about today, we believe is the flywheel. It is the fundamental piece that is critical to making the others work. Those goals weren't just about getting the results, it was about investing in our people. We knew from the start that brute force wasn't going to work. Just having a few very talented and capable dreamers wasn't going to get the results we needed. We needed technology, and it was important but it wasn't sufficient to achieve our goals. So that's where we really wanted to get this employee population who is inspired by what's possible, not having the fear around what the future looks like. We approached this not only with process change but also with cultural change, balancing between the two. Talking about the process for a moment, we approached our AI goals in the same way we build products. We understand where we are today, we define a bold vision for the future, we assess the different opportunities, prioritize them, and we put structure around them. For each of the initiatives we have goals, accountability, celebrations where we encourage, and the learning along the way. We put structure and governance around it. We had a small team of people who led from the center, who really said we're going to make this happen. They day in and day out are living and breathing AI and still continue to do so, helping drive that change. Investing in a long-term goal is hard. Choosing to invest in AI as a disruptor is hard to do. It requires clarity, courage, and commitment. For us it started at the top. Melissa, who is now here, made this one of her top goals. It's a goal that she's accountable to, and it's a goal that we as the executive leadership are accountable to, and we cascaded it through the organization. That sent a really powerful message that we do have to deliver on the short term but we also need to invest in the long term, and we believe that this is an important investment for the long term. That accountability from the top and that commitment is really important for driving the type of cultural change we're looking for. So we had goals but we had to capture the hearts and minds of our employees. Where did we start? In 2023, we started with the basics. We had AI training, the fundamentals of AI, that we asked employees to take. This was really important to get everyone on the same playing field. Knowledge is power, and by having this fundamental training it helped people understand what we were doing with AI, the basics of technology, the fact that we had governance around it, and that we were being responsible with our data and our customers' data. That was a really important level setting. We also thought it was really important that people understood that AI would be an accelerant for WEX, but also for themselves. It wasn't about disrupting people's jobs, it was about helping simplify the business of doing business for our customers and for ourselves. So we had the training out there quickly. We realized the training was really good and it was an important foundation and place to start, but it wasn't enough. Because if you talk to even the smartest people in the room, the first time you use gen AI, it's not going to magically work. You have to work at it, you have to experiment with it. We knew it took a lot of hours of experimentation and even more to actually build a habit and drive systemic change. So the next thing we did, in partnership with Google, we set up some optional hands-on sessions for people to sign up. Forty people at a time could sign up for hands-on practice, and we were over-subscribed every time. We've probably done 20 or more sessions now. What the sessions are is essentially people coming in, getting real-world examples, seeing how prompts work, how you write them, how you provide context, how you iterate, and then they actually go and do it themselves in that session with coaching. They're getting that real-world experience that supports the theory behind it. Then we ask people to commit. We say, 'Hey, every day once a day, go and use a gen AI tool. Make it part of your practice where you're turning to this technology to help you do your work.' With that, we found those employees who went through this hands-on training are more likely to use AI, and they feel more comfortable that WEX has responsible AI and governance in place. As you may have heard this morning, three out of four of our employees are using gen AI tools on a regular basis, which is pretty awesome. From there, as we round out 2024, we're continuing to adopt, adapt, pivot as needed. I want to close with three lessons we've learned. First, make employees the hero. Everyone likes to be recognized, and we often recognize outcomes when people have finished a project or delivered a meaningful result, but we sometimes forget to recognize the fearless along the way, the learning that people are going through, the contrarians, the experimenters. We've been doing that at WEX, celebrating the journey, not just the outcome. One of the things we've done is declare a group of 100 AI accelerators at WEX. These accelerators are mid-level people who either raised their hand or were nominated by their peers. Before they were anointed to be an AI accelerator, they had to pass three criteria. First, they're actually experimenting with AI. Second, they have the right mindset, thinking about what's possible. Third, they're influencers, they have that experimental, entrepreneurial attitude, they are curious, excited, willing and able to go talk to others in the organization and be advocates of AI. We actually have one, she's not in our session today, but one of our AI accelerators did a bingo. If you did a certain number of things, you could win a pass to join us here at this conference. Eileen's here, and I was talking to her this morning. She told me a really cool story. She was talking to one of the EAs a couple of weeks ago at WEX, and the EA said, 'I'm really nervous that I'm going to lose my job in a couple of years because I could be replaced by AI. I had this retirement plan, and I don't know if I'll get enough years.' Eileen sat down with her and said, 'Let's pull up AI and talk about how your job will be better, and you'll be better at your job with AI.' They went through this together using gen AI, and at the end the woman called her husband and said, 'I don't have to retire early. This is actually going to make me so much better.' The reality is I probably never would have known about this woman who had her fears, but our AI accelerator was out there talking to the audience and to the employees, helping alleviate the fears. The second lesson is lead by example. I believe it is up to me and to all of you, frankly, to get into the trenches on this one, to use the tools, to experiment, to figure out what works and what doesn't work. In doing so, we're going to have successes and failures. I think it's really important to be vulnerable and talk about what didn't work. A quick story: we were in a meeting a couple of months ago and we wanted to do some competitive analysis. Someone said it's going to take two weeks. I said, 'Can we just pull up gen AI and see how it goes?' They played with it and said, 'I can actually do this in two days.' Now the next time it came up, they said, 'I've got a better way to do this. It's faster, more productive, we're able to cover more competitors.' The third lesson is drive accountability at every level. This is like trying to be healthy. You say yes, I'm going to drink water every day, I'm going to exercise, but it takes a lot to build a habit. Because there aren't a lot of established practices out there, it's harder to build habits in AI. But if you commit to doing it, it does become your habit. To help build those habits, we're putting a little tension in the system. As a leadership team, and I am not exempt from this, we have a goal of 10% productivity improvement for each of our functions. The tension we put in the system is once a month we have to report out to our peers and to Melissa on what we're doing. For the digital org, which is my org, I have four groups working on this: product management, innovation, design, and product marketing. They have a goal of 10% productivity. One quick story about how cool this was: one of our objectives is to talk to customers more and get qualitative feedback, but it's hard to find time to talk to customers and for customers to find time to talk to us. One junior designer in our org took it upon herself, not asked by anyone, and started using synthetic AI to get that voice of customers. She did it once, it was pretty cool. She's been experimenting with it, and now she can get 10 times the feedback in two weeks with 70% accuracy, and it's climbing every day. This is enabling us to get so much more customer feedback than we've ever been able to do. What's really cool is it's her who's talking about it, and her peers are listening. It was on an experience review, and now it's getting traction because of it. There's accountability and then there's celebrating those who are using it to drive momentum. As I wrap up here, AI isn't the future, it's the present. The real innovation lies in how we can harness the power and partner with AI to improve our skills, which will free us up to do more creative thinking, problem solving, connect more with each other. Here's my challenge to you, and I'll leave you with this thought: Don't wait for AI to happen. Make it happen. Set a bold goal, experiment, learn, encourage others to do so. You may not, you probably won't, hit the goal exactly as you had planned, but the learnings along the way will propel your organization forward in ways you wouldn't have imagined, and in doing so, drive the outcomes you're expecting and shape the future of work.